Money View Fintech Backend Engineer Interview: Rounds, Questions and Preparation

What the job involves

As a backend engineer at a neobanking, lending, or insurtech company like Money View Fintech, you will build and maintain server-side systems that power loan origination, credit underwriting, repayment processing, and customer account management. Day to day, you will write APIs, work with databases, integrate with payment gateways and credit bureaus, and ensure high availability and data security for financial transactions. You will also collaborate with product, risk, and compliance teams to translate business rules into reliable code.

Role and Technical Knowledge

1. 1

   How would you design a REST API for a loan application submission in a lending app?

   A strong answer covers endpoint structure, request validation, idempotency, secure data handling, and integration with underwriting services.

2. 2

   Explain how you would ensure data consistency when a customer repays a loan and the payment status must update across multiple services.

   Discuss transactions, eventual consistency, idempotent operations, and using message queues or sagas for distributed systems.

3. 3

   What are the key security considerations when storing customer KYC documents and financial data?

   Mention encryption at rest and in transit, access controls, audit logs, compliance with RBI guidelines, and tokenization of sensitive data.

4. 4

   How would you integrate a credit bureau API into your backend to fetch a customer's credit score?

   Cover API authentication, error handling, caching, rate limiting, and fallback mechanisms if the bureau is unavailable.

Practical Scenarios

1. 5

   Imagine a payment gateway callback fails after a successful transaction. How would you handle this to avoid double crediting or missing a repayment?

   Propose idempotent callback handlers, reconciliation jobs, and status polling with the gateway to ensure consistency.

2. 6

   You need to add a new feature for instant loan disbursement. Outline the backend changes and potential risks.

   Focus on API changes, real-time bank integrations, fraud checks, transaction limits, and rollback plans.

3. 7

   A sudden spike in loan applications causes your database to slow down. How would you diagnose and resolve it?

   Discuss query optimization, indexing, read replicas, caching, and horizontal scaling strategies.

4. 8

   How would you design a system to send automated payment reminders to borrowers via SMS and email without spamming them?

   Cover scheduling, user preferences, rate limiting, and tracking delivery status with retries.

Behavioural and HR

1. 9

   Why do you want to work in fintech, specifically in neobanking or lending, rather than a general tech company?

   Show interest in financial inclusion, the impact of technology on credit access, and awareness of challenges like regulation and trust.

2. 10

   Describe a time you had to learn a new technology quickly for a project. How did you approach it?

   Highlight self-learning, resourcefulness, and applying the new skill to deliver results under time pressure.

3. 11

   Tell me about a situation where you had to work in a team to solve a complex problem. What was your role?

   Use the STAR method to show collaboration, communication, and your specific contribution to the outcome.

4. 12

   How would you handle a situation where you disagree with a senior engineer on a technical decision?

   Emphasize respectful discussion, data-driven arguments, and willingness to align with team decisions once made.

Coding and Problem Solving

1. 13

   Write a function to detect if a given list of transactions contains a cycle of debits and credits that nets to zero.

   This tests graph or hashmap skills; a strong answer explains the approach, edge cases, and time complexity.

2. 14

   Given a stream of loan repayment events, how would you calculate the outstanding balance for a customer in real time?

   Discuss event sourcing, incremental updates, and handling out-of-order events with timestamps.

3. 15

   Implement a rate limiter for an API endpoint that allows a maximum of 100 requests per minute per user.

   Cover token bucket or sliding window algorithms, distributed caching with Redis, and handling race conditions.

4. 16

   How would you find the top 5 customers with the highest number of late payments from a large transaction table?

   Focus on SQL aggregation, indexing, and efficient query writing; mention partitioning for large datasets.